Using Data Envelopment Analysis in Credit Risk Evaluation of ICT Companies

Michaela Kavčáková and Kristína Kočišová

AGRIS on-line Papers in Economics and Informatics, 2020, vol. 12, issue 4

Abstract: The aim of the paper is to explore possibilities of diagnosis corporate credit risk through DEA and design an appropriate model for diagnosis of credit risk, which can be used in different sectors of national economy (e.g. agricultural, service sector or industry and innovation sector). The model differs from the conventional application of DEA because of variables selection and construction of production-possibility frontier. We illustrate application of models on sample 110 randomly selected companies during the 2013-2017 period. The reason for choosing the ICT companies is the fact that this sector is considered to be driving force behind the growth of the economy. The data has been obtained from Finstat. The results are divided into identification of 3 zones of corporate financial health with a different stage of credit risk. They show that DEA achieves a satisfactory value of a correct classification into the relevant zone (financial health, grey, and financial distress zone), but also the relatively high error rate of the DEA in the identification of companies in financial distress.

Keywords: Research Methods/Statistical Methods; Risk and Uncertainty (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:ags:aolpei:320237

DOI: 10.22004/ag.econ.320237

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